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Until now, we have only used our framework for ChEBI, but in principle, it should also be applicable to other data sets and prediction tasks. One such task is the prediction of protein functions as sp…
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Hello,
Thank you again for your help in my previous issue. I can finally run the ProtST task on my cluster using one GPU. However, I need clarification about the command that you provided.
I wan…
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Thank you for sharing TMbed! I noticed there isn’t a training script in the repository, and I had a question regarding the cross-entropy loss function used.
From the paper, it seems like TMbed might …
grmos updated
2 weeks ago
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https://doi.org/10.1101/103994
> As high-throughput biological sequencing becomes faster and cheaper, the need to extract useful information from sequencing becomes ever more paramount, often limit…
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Hi! Thank you for this amazing tool, also for the easy installation! I was wondering if there is any easy way of generating more than 5 models per case, besides looping over the execution of run_infer…
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Databases annotated as software, see the guidelines "Database versus software" section on deciding based on the context if a database should be annotated or not (usually not!). This is the most freque…
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Good morning,
I would like to propose you to share another extremely useful example of AF2 usage. Many scientists are using protein embeddings for downstream tasks (i.e. function prediction). [AF2 …
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After migrating from [bio_embeddings](https://github.com/sacdallago/bio_embeddings) to calculate embeddings directly in biotrainer for the provided sequences, it is now theoretically possible to allow…
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Hi everyone,
I’m fairly new with huggingface, and I was wondering if it is possible to locally fine tune SaProt with the SaProtHub datasets, and how to call the models from there as well, rather t…
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https://doi.org/10.1101/168120 (http://www.biorxiv.org/content/early/2017/07/25/168120)
> Accurate annotation of protein functions is important for a profound understanding of molecular biology. A …